As the Internet rapidly scales in size, capacity, and capability, a growing number of computing and communication services are migrating to a common Internet Protocol (IP). This in turn results in an increased demand for highly reliable and effective IP service management schemes, where accurate network topology information is of critical importance.
Driven by this need, network topology inference is an activity which has received a significant amount of interests from both the research community and industry during the last decade. Consequently, a number of schemes have been developed for estimating network routing trees for both multicast and unicast traffic in a given IP network. Their underlying topology-discovering mechanisms have generally evolved from traceroute-based techniques to those employing more sophisticated metrics including hamming distance, fan-out, inter-packet delay variance, and additive metrics (e.g., loss, delay, and utilization).
Unfortunately however, topologies determined using existing methods generally treat each single link as a logical link which may actually correspond to multiple physical layer-3 devices and their interconnecting links in the actual network. Consequently, the resulting topologies so determined are generally unsuitable for applications (such as fine-grained anomaly localization) where detailed topology information is required.